class TensorflowLite::Image::PoseEstimation::Output

Included Modules

Defined in:

tflite_image/pose_estimation/output.cr

Constant Summary

LINES = [[BodyJoint::LeftEar, BodyJoint::LeftEye, BodyJoint::Nose, BodyJoint::RightEye, BodyJoint::RightEar], [BodyJoint::LeftWrist, BodyJoint::LeftElbow, BodyJoint::LeftShoulder, BodyJoint::RightShoulder, BodyJoint::RightElbow, BodyJoint::RightWrist], [BodyJoint::LeftShoulder, BodyJoint::LeftHip, BodyJoint::LeftKnee, BodyJoint::LeftAnkle], [BodyJoint::RightShoulder, BodyJoint::RightHip, BodyJoint::RightKnee, BodyJoint::RightAnkle], [BodyJoint::LeftHip, BodyJoint::RightHip]]

Constructors

Instance Method Summary

Instance methods inherited from module TensorflowLite::Image::Detection::Points

adjust(canvas_width : Int, canvas_height : Int, offset_left : Int, offset_top : Int) adjust, make_adjustment(original_width : Int, original_height : Int, canvas_width : Int, canvas_height : Int, offset_left : Int, offset_top : Int) : Nil make_adjustment, points : Hash(String, Detection::Point) points

Instance methods inherited from module TensorflowLite::Image::Detection::Lines

lines : Indexable(Detection::Line) lines

Instance methods inherited from module TensorflowLite::Image::Detection

associated : Array(Detection) associated, associated=(associated : Array(Detection)) associated=, label : String | Nil label, markup(image : Canvas, minimum_score : Float32 = 0.3_f32, font : PCFParser::Font | Nil = nil, color = StumpyPNG::RGBA::WHITE) : Canvas markup, type : Symbol type

Constructor methods inherited from module TensorflowLite::Image::Detection

new(ctx : YAML::ParseContext, node : YAML::Nodes::Node)
new(pull : JSON::PullParser) new

Constructor Detail

def self.new(points : Array(PoseEstimation::Point)) #

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Instance Method Detail

def label : String | Nil #

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def lines : Indexable(Detection::Line) #

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def markup(image : Canvas, minimum_score : Float32 = 0.3_f32, font : PCFParser::Font | Nil = nil, color = StumpyPNG::RGBA::WHITE) : Canvas #

add the detection details to an image

if marking up the original image, you'll need to take into account how it was scaled and provide offsets


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def points : Hash(String, Detection::Point) #

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def type : Symbol #
Description copied from module TensorflowLite::Image::Detection

i.e. object, pose, face, age, class


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